Answer / Archit Vishnoi

Autoencoders are a type of neural network used for learning efficient data representations. They consist of an encoder (which maps the input to a lower-dimensional space) and a decoder (which maps the lower-dimensional representation back to the original space). The goal is to learn a compact yet informative representation of the input data, which can be useful for tasks like dimensionality reduction, anomaly detection, and generating new data.

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